A global evaluation model applied to wind power plant site selection

Meysam Asadi, Mohsen Ramezanzade and Kazem Pourhossein

Applied Energy, 2023, vol. 336, issue C, No S0306261923002040

Abstract: Site selection is one of the most critical steps in designing wind farms due to the heterogeneous distribution of wind energy on the Earth’s surface. Additionally, the wind power site selection problem is a complex process since it must be evaluated from multiple perspectives, including techno-economic, social, and environmental factors. In this regard, the current study proposes a new approach which combines Full Factorial Design and Analytic Hierarchy Process. The output of this combination creates a global model for the site selection of wind power plants. Using this model, the decision-making space is transformed into the scoring space which makes the scores related to candidate sites more meaningful and understandable. Therefore, Iran is selected to find suitable wind sites to reveal the proposed model’s capability. The results indicate that approximately 1300, 5109, and 16000 km2 of the study area are considered outstanding, excellent, and good for the utilization of wind energy. Furthermore, a functional analysis was conducted to ensure that the proposed model was robust, and accordingly, the accuracy of siting some existing wind farm sites was also studied. Based on the calculated scores, some real sites, e.g., Khaf and Manjil, are suitable for wind power development. Some sites could be more carefully selected, like the Binaloud wind site; others have not been appropriately selected, such as the Soffeh, Shiraz, and Sarab sites. Finally, the model can be employed worldwide as a standard index for assessing wind farm site quality.

Keywords: Wind energy; Site selection; GIS; Full Factorial Design (FFD); AHP; Model design (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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DOI: 10.1016/j.apenergy.2023.120840

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